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2223224

Project Grant

Overview

Grant Description
Sbir Phase I: A Human-Aware Platform for Socially Collaborative Personal Artificial Intelligence (AI) Assistants -The broader impact of this Small Business Innovation Research (SBIR) Phase I project is enabling artificial intelligence (AI) assistants to become proactive, empowering them to provide better service to users.

Currently, commercial AI assistants respond to user requests reactively. The technologies developed in this project would provide AI assistants with the situational awareness to understand users' lives and predict their needs. The technology will also enable social intelligence to take the initiative to support users in appropriate ways.

This SBIR Phase I project will apply these technologies to a consumer product for assisting users with time management and meeting goals while establishing and strengthening healthy, desirable habits in their daily lives. Proactive personal AI assistants have the potential to improve productivity, convenience, and quality of life for every person, as well as to promote aging in place with greater independence and wellness.

Fundamental scientific advancements will also enable a new generation of potential applications for AI assistants across sectors, fueling economic growth and creating jobs. This project addresses two central technical challenges for enabling proactive AI assistants: contextual awareness of users and agent-initiated interaction.

Contextual awareness includes the AI agent's real-time understanding of current user state and activity, as well as a long-term understanding of past user habits. The project proposes to develop hybrid computational models combining machine learning of multimodal user observations from visual, acoustic, and geolocation data with probabilistic graphical models that perform long-term inference and prediction over historical user observations.

A virtually-embodied AI agent will leverage these contextual awareness representations to conduct real-time, face-to-face collaborations with users. The project proposes to research and develop a dynamic scheduling approach to proactively enable the agent to communicate with users.

These models will be integrated within a broader system that assists users with time management. This system will implement an end-to-end architecture for protecting user privacy while handling their data. The technical solution will be validated based on quantitative metrics related to utility and user acceptance by deploying the prototype in end users' homes over a multi-week period and conducting surveys about their subjective experience of the proactive AI assistants.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Awarding / Funding Agency
Place of Performance
San Francisco, California 94108-3226 United States
Geographic Scope
Single Zip Code
Related Opportunity
None
Applied Sentience was awarded Project Grant 2223224 worth $275,000 from National Science Foundation in May 2023 with work to be completed primarily in San Francisco California United States. The grant has a duration of 1 year and was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.

SBIR Details

Research Type
SBIR Phase I
Title
SBIR Phase I:A Human-Aware Platform for Socially Collaborative Personal Artificial Intelligence (AI) Assistants
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is enabling Artificial Intelligence (AI) assistants to become proactive, empowering them to provide better service to users. Currently, commercial AI assistants respond to user requests reactively. The technologies developed in this project would provide AI assistants with the situational awareness to understand users’ lives and predict their needs.The technology will also enable social intelligence to take the initiative to support users in appropriate ways. This SBIR Phase I project will apply these technologies to a consumer product for assisting users with time management and meeting goals while establishing and strengthening healthy, desirable habits in their daily lives. Proactive personal AI assistants have the potential to improve productivity, convenience, and quality of life for every person, as well as to promote aging in place with greater independence and wellness. Fundamental scientific advancements will also enable a new generation of potential applications for AI assistants across sectors, fueling economic growth and creating jobs. _x000D_ _x000D_ This project addresses two central technical challenges for enabling proactive AI assistants: contextual awareness of users and agent-initiated interaction. Contextual awareness includes the AI agent’s real-time understanding of current user state and activity, as well as a long-term understanding of past user habits. The project proposes to develop hybrid computational models combining machine learning of multimodal user observations from visual, acoustic, and geolocation data with probabilistic graphical models that perform long-term inference and prediction over historical user observations. A virtually-embodied AI agent will leverage these contextual awareness representations to conduct real-time, face-to-face collaborations with users. The project proposes to research and develop a dynamic scheduling approach to proactively enable the agent to communicate with users. These models will be integrated within a broader system that assists users with time management. This system will implement an end-to-end architecture for protecting user privacy while handling their data. The technical solution will be validated based on quantitative metrics related to utility and user acceptance by deploying the prototype in end users’ homes over a multi-week period and conducting surveys about their subjective experience of the proactive AI assistants._x000D_ _x000D_ This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Topic Code
HC
Solicitation Number
NSF 22-551

Status
(Complete)

Last Modified 5/4/23

Period of Performance
5/1/23
Start Date
4/30/24
End Date
100% Complete

Funding Split
$275.0K
Federal Obligation
$0.0
Non-Federal Obligation
$275.0K
Total Obligated
100.0% Federal Funding
0.0% Non-Federal Funding

Activity Timeline

Interactive chart of timeline of amendments to 2223224

Additional Detail

Award ID FAIN
2223224
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
CMF5RHMGBN91
Awardee CAGE
93FF6
Performance District
11
Senators
Dianne Feinstein
Alejandro Padilla
Representative
Nancy Pelosi

Budget Funding

Federal Account Budget Subfunction Object Class Total Percentage
Research and Related Activities, National Science Foundation (049-0100) General science and basic research Grants, subsidies, and contributions (41.0) $275,000 100%
Modified: 5/4/23